Assessing efficacy of antiviral therapy for COVID-19 patients: A case study on remdesivir with bayesian synthesis design and multistate analysis
Sih-Han Liao, Chien-Ching Hung, Chiung-Nien Chen, Jui-Yi Yen, Chen-Yang Hsu, Amy Ming-Fang Yen, Chi-Ling Chen
Journal of the Formosan Medical Association, doi:10.1016/j.jfma.2021.04.026
Bayesian synthesis sequential design remdesivir. A multistate model was developed to model the dynamics of hospitalized COVID-19 patients from three transient states of low, medium-, and high-risk until the two outcomes of recovery and death. The outcome measures for clinical efficacy comprised high-risk state, death, and discharge. Results: The efficacy of remdesivir in reducing the risk of death and enhancing the odds of recovery were estimated as 31% (95% CI, 18e44%) and 10% (95% CI, 1e18%), respectively. Remdesivir therapy for patients with low-risk state showed the efficacy in reducing subsequent progression to high-risk state and death by 26% (relative rate (RR), 0.74; 95% CI, 0.55e0.93) and 62% (RR, 0.38; 95% CI, 0.29e0.48), respectively. Less but still statistically significant efficacy in mortality reduction was noted for the medium-and high-risk patients. Remdesivir treated patients had a significantly shorter period of hospitalization (9.9 days) compared with standard care group (12.9 days).
Conclusion: The clinical efficacy of remdesvir therapy in reducing mortality and accelerating discharge has been proved by the Bayesian synthesis design and multistate analysis.
Role of funder/sponsor The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Declaration of competing interest The authors have no conflicts of interest relevant to this article.
Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.jfma.2021.04.026.
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